Neural networks and brain function

• Simplified model of neurons and synapses

• Parallel implementation

• Information and processing are distributed across the network (hence graceful degradation) ... but problems -

• NNs contain only local control. In the brain, local activity is constantly broadcast over short and long distances.

• Restrictions on architecture - eg. layers and hidden units

• Scaling problem

• Catastrophic interference of new with old learning

• Finally, the ``neurons'' are usually macroscopically defined entities - could be hypotheses, goals, properties - see the Ralph Morelli example. Also they are idealised or ``mathematically pure''.

Thus the neural model is still more of an inspiration than a modelling at the level of mechanism.